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What Metrics Predict Candidate Success?

January 22, 2019

Recruiting is often a numbers game, and the numbers aren’t always promising for employers. For instance, the average cost to hire one employee ranges from $4,000 to $7,645, depending on the types of companies studied, says Aleks Peterson at Glassdoor.

Companies average six weeks to fill a position, says Peterson, during which time productivity is down. If the goal is to replace someone in an existing position rather than to fill a newly-created position, the costs can be even higher: 50 percent of annual salary for an entry-level worker, 125 percent of salary for a mid-level worker and up to 250 percent of salary for an executive, says Bill Conerly at Forbes.

Your people are valuable, and losing them can be costly. In a data-driven world, recruiters and hiring managers can track dozens or even hundreds of variables related to job candidates. But which of these numbers shed light on success — and which ones just clutter up your recordkeeping?

What Are Recruiting Metrics and Why Track Them?

Tracking metrics that are relevant to your company’s hiring goals can help companies better understand and improve their hiring processes, says Erik van Vulpen, founder of the Analytics in HR blog.

Because hiring is a human-centered process, recruiters and hiring managers can struggle to think about their work in quantitative terms, says Archana Jerath at the Society for Human Resources Management (SHRM). Yet doing so can bring immense value to the hiring process.

For instance, research indicates that a 5-percent increase in employee engagement translates to a 3-percent growth in company revenue, Meghan M. Biro writes at Forbes. Improved engagement can also reduce turnover, thereby lowering the cost of recruitment.

Metrics can be used to understand why certain candidates succeed, who is most likely to accept a job offer and what characteristics help employees do well within the organization. They can also help companies speed up the hiring process in order to keep top candidates engaged and reduce the costs of unfilled positions.

Several metrics have proven themselves as valuable when it comes to understanding why and how candidates succeed on the job. To build a candidate success profile based on available data, keep these elements in mind:

Time to Fill and Time to Hire

While these sound similar, time to fill and time to hire focus on two separate questions:

Time to fill measures the time between the moment the company realizes it needs a new employee and that new employee’s start date.

Time to hire measures the time between the moment a particular candidate first contacts the company and their start date.

Time to fill helps companies determine whether they’re moving quickly enough to address their staffing needs. A long time to fill indicates that the hiring team may not be planning or sourcing candidates effectively, or that attempts to reach out to qualified candidates are failing.

Cost Per Hire

Cost per hire remains one of the most popular and helpful human resources metrics, says Jenna Puckett at Technology Advice. This metric is calculated by adding together the costs of internal and external hiring efforts, then dividing that sum by your total number of hires.

Cost per hire helps companies determine whether their recruitment spending is realistic for the company’s budget, size, industry and location, Puckett says. When combined with other factors, it can also help a company measure the value of certain hiring decisions: High-quality hires for a relatively low cost per hire offer tremendous value.

Time to Productivity

Once a new hire arrives for their first day of work, how long does it take for that person to reach an expected level of productivity on the job?

All jobs have learning curves. Tracking time to productivity helps a company understand how effective its onboarding processes are, says Michael Schneider, human capital specialist at Welltower. When combined with other metrics, time to productivity can also help recruiters and hiring managers spot patterns in the quality of the recruiting process and in candidate preparedness.

Turnover

Employees can’t succeed with a company if they don’t stay at the company. That’s why turnover is one of the central metrics to understanding employee success.

It’s valuable to track voluntary and involuntary turnovers separately, the team at Friday Feedback says. Involuntary turnover based on disciplinary dismissals are particularly valuable, since they can help companies spot mistakes in the hiring process or in internal processes and procedures.

Tracking voluntary separation can be helpful, too: Understanding why an employee chooses to leave can reveal why the employee was a poor fit for the company and how the hiring process can help spot similar poor fits in the future.

Quality of Hire

How well are your new hires doing on the job? To measure success by more than just longevity, take a look at quality of hire.

Like ratios, quality of hire isn’t always a single metric. Rather, it is often “a collection of data points that are indicative of a successful hire,” says Sushman Biswas, associate editor at HR Technologist. To reduce this collection down to a single number, Biswas says, divide the sum of the selected data points by the number of selected data points.

One way to make the numbers more manageable is to use a rubric to evaluate employee performance, says Jennifer Ritter at Digitec Interactive. The rubric allows managers to assign a point value to key tasks, making it easier to quantify the quality of an employee’s work and to compare their performance over the past year with that of other employees.

The Future of Candidate Success Metrics

Currently, recruiters and hiring managers use metrics to understand and influence human behavior. They shed light on human candidates, suggest human responses to problems and provide support for proposals and funding requests provided to humans.

Artificial intelligence may soon introduce a non-human element to the analysis of hiring metrics. For instance, advances in pattern-matching technology have made it possible for AI to more accurately predict whether a new hire will stay in the job longer than a year, Terena Bell writes at CIO.

AI may also be able to track metrics that influence human staff members, but that aren’t currently tracked by most companies. A study by researchers Sarah Kathryn Stein, Amir Goldberg and Sameer B. Srivastava found that candidates were more likely to be hired when their written answers to interview questions used language that matched that used by previously hired employees. While the average recruiter or hiring manager may not notice the pattern, AI can. By doing so, the software can alert its users to patterns they can track for better hiring.

While Bell notes that the AI can’t predict the specific day an employee will quit, rapid advances in technology have made it possible for recruiters and hiring managers to track and analyze metrics based on ever-expanding datasets.

As these tools continue to develop, so will the ways in which recruiting teams can examine and compare various metrics — all of which can help improve the hiring process.